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Comment by throwaway13qf85 | Hacker News Reader

Does anyone know if this is any good? I don't think that Packt is a particularly reputable publisher. They published a similar book about Haskell (called "Haskell Financial Data Modelling and Predictive Analytics") which was absolutely terrible - useless for learning anything about Haskell, finance, data modelling or predictive analytics.

You can find a commentary on that book here on Reddit[0].

I hope this book is better, but I will withhold judgement until someone comes along who's read it and is able to give an informed opinion.

[0] http://www.reddit.com/r/haskell/comments/1rj2jq/book_haskell...

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The modelling the book covers is the best of the best. Not sure about the content of the book itself, but the Finances seem straight on.

I don't think I would call CAPM, the Fama-French 3-factor model, VaR, Black-Scholes and GARCH "the best of the best".

I would probably call the selection of topics "finance basics that no one in industry uses any more".

It may be suitable as a beginner's guide if the quality of the exposition is good enough, but my suspicion is that you would be better off getting a copy of "Python for Data Analysis" and a decent quant finance textbook.

Recommendations on the latter?

First of all, there's no "decent quant finance book" in existence.

But there are attempts at it. Most notable are:

- "An Introduction to the Mathematics of Financial Derivatives", by Neftci

- Wilmott books aren't bad.

- Brigo's "Interest Rate Models" is... flaky. It is a lot of material and seems to be quite rigorous, until some point most crucial for understanding, which gets skipped over. The interviews with traders at the end are good.

- Only buy Choudhry books, if you want to talk good about finance.

Investment Science by Luenberger

The gold standard for quant books: Hull's Options, Futures, and Derivatives.

http://www.amazon.com/Options-Futures-Derivatives-DerivaGem-...

This is very much a beginner's book. When I interviewed for internships in the summer of 2008, the interviewers expected that I would already be familiar with a large portion of the content of this book.

It really depends on what you're trying to achieve. The skills and knowledge necessary for long-term equity investment, short-term statistical arbitrage, derivative pricing and high-frequency trading are all quite different.

I dunno... Looking through the table of contents there's pretty good coverage of a lot of very specific research that goes well beyond basic capm/ff/var/bs/garch.

The goal of this book is clearly not going to be to teach you finance but rather to provide you with enough of the basics and beyond so you basically have all the tools needed to move forward.

Was very pleasantly surprised to see some of the stuff in the table of contents (ie. Pastor and Stambaugh's liquidity measure).

Will order this as I think it'll be a great reference.

"No one in the industry uses anymore"? Really?

Fama and French are still industry leaders, and they use the three factor model as the foundation of all of their portfolio management at Dimensional Fund Advisors, hands down the most successful mutual fund in existence. http://us.dimensional.com/process/multifactor.aspx

They continue to out-perform active fund managers, and they power a boat load of the investments for many American Corporations. And those American Corporations love to watch their money grow.

What makes you think these models don't still power successful financial products today?

I highly doubt Dimensional are using a three factor model to manage their portfolios. Typical multi-factor models these days can have anywhere from 10 to 100 factors.

The concepts of the three factor model are important to learn but implementing one in practice is rarely done. These core factors are too crowded these days as all the quant funds are looking at the same factors.

You're talking about active management. That is not what DFA does so you clearly don't get the philosophy.

The page you linked to is Dimensional explaining their five factor model, and it sounds like they only use that as a basis for a more complicated model.

The very example you gave to support your point actually detracts from it.

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